Singularity-free planning for a robot cat free-fall with control delay: Role of limbs and tail

Sadati, S. M. Hadi; Meghdari, Ali

doi:10.1109/icmae.2017.8038645

Cited by 5 publications

(4 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, the results in [24], [25], [26] show that a tailed robot can effectively accomplish inertial reorientation in at least one plane. The in-depth analysis of [27] and the simulations in [28] concluded that the use of a tail or appendages is particularly interesting for terrestrial robots and also explored the use of flailing limbs. However, although such inertial devices can be effectively integrated in some robot designs, it might not always be possible or desirable to add dedicated appendages such as multiple-degree-of-freedom (DOF) tails or joints with an infinite range of motion.…”

Section: Global Rotationmentioning

confidence: 99%

Design and Experimental Validation of Reorientation Manoeuvres for a Free Falling Robot Inspired From the Cat Righting Reflex

Garant

Gosselin

2021

IEEE Trans. Robot.

View full text Add to dashboard Cite

This paper presents two distinct manoeuvres allowing an articulated robot in free fall to change its orientation using closed paths in the joint space. It is shown through dynamics simulations that the magnitude of the net rotation is dependent upon the amplitude of the angular displacement of the joints. With realistic joint limitations, the robot, which includes rotary actuators only, can perform a 180-degree reorientation about its longitudinal axis, similar to the cat righting reflex. The second manoeuvre allows the robot to accomplish rotations of smaller magnitude about a different axis. A physical prototype and a VICON motion tracking system are used to experimentally validate the simulation results. Finally, it is shown that the two manoeuvres, which yield rotations about fixed axes, can be repeated and alternated to enable the robot to reach any arbitrary 3D orientation.

show abstract

Section: Global Rotationmentioning

confidence: 99%

Design and Experimental Validation of Reorientation Manoeuvres for a Free Falling Robot Inspired From the Cat Righting Reflex

Garant

Gosselin

2021

IEEE Trans. Robot.

View full text Add to dashboard Cite

show abstract

“…We have recently developed a Matlab software package, called AutoTMTDyn to derive the TMT EOM of rigid-body mechanisms (Sadati et al, 2015, 2018d). AutoTMTDyn 1 was originally developed for deriving the TMT EOM of rigid-body systems (Sadati et al, 2015) and used for analyzing free-fall righting maneuvers of a robot cat (Sadati and Meghdari, 2017), lumped system modeling of a continuum appendage (Sadati et al, 2017b), and dynamic analysis of a spider web structure (Sadati et al, 2018a).…”

Section: Review Of the State Of The Artmentioning

confidence: 99%

TMTDyn: A Matlab package for modeling and control of hybrid rigid–continuum robots based on discretized lumped systems and reduced-order models

Sadati

Naghibi

Shiva

et al. 2020

The International Journal of Robotics Research

View full text Add to dashboard Cite

A reliable, accurate, and yet simple dynamic model is important to analyzing, designing, and controlling hybrid rigid–continuum robots. Such models should be fast, as simple as possible, and user-friendly to be widely accepted by the ever-growing robotics research community. In this study, we introduce two new modeling methods for continuum manipulators: a general reduced-order model (ROM) and a discretized model with absolute states and Euler–Bernoulli beam segments (EBA). In addition, a new formulation is presented for a recently introduced discretized model based on Euler–Bernoulli beam segments and relative states (EBR). We implement these models in a Matlab software package, named TMTDyn, to develop a modeling tool for hybrid rigid–continuum systems. The package features a new high-level language (HLL) text-based interface, a CAD-file import module, automatic formation of the system equation of motion (EOM) for different modeling and control tasks, implementing Matlab C-mex functionality for improved performance, and modules for static and linear modal analysis of a hybrid system. The underlying theory and software package are validated for modeling experimental results for (i) dynamics of a continuum appendage, and (ii) general deformation of a fabric sleeve worn by a rigid link pendulum. A comparison shows higher simulation accuracy (8–14% normalized error) and numerical robustness of the ROM model for a system with a small number of states, and computational efficiency of the EBA model with near real-time performances that makes it suitable for large systems. The challenges and necessary modules to further automate the design and analysis of hybrid systems with a large number of states are briefly discussed.

show abstract

“…Special tails were added to help robot jumping ( Zhao et al, 2013 ), insect-sized robot achieving more rapid orientation ( Singh et al, 2019 ), and more complicated tails (e.g., a three-segment prototype ( Liu and Ben-Tzvi, 2020 )) and soft tails ( Butt et al, 2021 ) were designed to perform as real tails, which is not rigid in reality. 2) Using the whole body to reorient body posture (or attitude) ( Kane and Scher, 1969 ; Sadati and Meghdari, 2017 ; Liu et al, 2020 ; Yim et al, 2020 ): In this kind of research, models do not need a special part that absorbs extra angular momentum, instead, the control strategy is to redistribute the angular momentum to different parts of the body to achieve different goals. For example, cats do not necessarily need their tails to change their body orientation in air ( Fredrickson, 1989 ).…”

Section: Introductionmentioning

confidence: 99%

“…2) Using the whole body to reorient body posture (or attitude) ( Kane and Scher, 1969 ; Sadati and Meghdari, 2017 ; Liu et al, 2020 ; Yim et al, 2020 ): In this kind of research, models do not need a special part that absorbs extra angular momentum, instead, the control strategy is to redistribute the angular momentum to different parts of the body to achieve different goals. For example, cats do not necessarily need their tails to change their body orientation in air ( Fredrickson, 1989 ).…”

Section: Introductionmentioning

confidence: 99%

On the dynamics and control of a squirrel locking its head/eyes toward a fixed spot for safe landing while its body is tumbling in air

Zhang

2022

Front. Robot. AI

View full text Add to dashboard Cite

An arboreal mammal such as a squirrel can amazingly lock its head (and thus eyes) toward a fixed spot for safe landing while its body is tumbling in air after unexpectedly being thrown into air. Such an impressive ability of body motion control of squirrels has been shown in a recent YouTube video, which has amazed public with over 100 million views. In the video, a squirrel attracted to food crawled onto an ejection device and was unknowingly ejected into air by the device. During the resulting projectile flight, the squirrel managed to quickly turn its head (eyes) toward and then keeps staring at the landing spot until it safely landed on feet. Understanding the underline dynamics and how the squirrel does this behavior can inspire robotics researchers to develop bio-inspired control strategies for challenging robotic operations such as hopping/jumping robots operating in an unstructured environment. To study this problem, we implemented a 2D multibody dynamics model, which simulated the dynamic motion behavior of the main body segments of a squirrel in a vertical motion plane. The inevitable physical contact between the body segments is also modeled and simulated. Then, we introduced two motion control methods aiming at locking the body representing the head of the squirrel toward a globally fixed spot while the other body segments of the squirrel were undergoing a general 2D rotation and translation. One of the control methods is a conventional proportional-derivative (PD) controller, and the other is a reinforcement learning (RL)-based controller. Our simulation-based experiment shows that both controllers can achieve the intended control goal, quickly turning and then locking the head toward a globally fixed spot under any feasible initial motion conditions. In comparison, the RL-based method is more robust against random noise in sensor data and also more robust under unexpected initial conditions.

show abstract

Singularity-free planning for a robot cat free-fall with control delay: Role of limbs and tail

Cited by 5 publications

References 25 publications

Design and Experimental Validation of Reorientation Manoeuvres for a Free Falling Robot Inspired From the Cat Righting Reflex

Design and Experimental Validation of Reorientation Manoeuvres for a Free Falling Robot Inspired From the Cat Righting Reflex

TMTDyn: A Matlab package for modeling and control of hybrid rigid–continuum robots based on discretized lumped systems and reduced-order models

On the dynamics and control of a squirrel locking its head/eyes toward a fixed spot for safe landing while its body is tumbling in air

Contact Info

Product

Resources

About